package com.zhang.spark_1.spark_core.operator.transform

import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

/**
 * @title:
 * @author: zhang
 * @date: 2021/12/5 18:51 
 */
object Spark06_RDD_Operator_Transform_Test3 {

  def main(args: Array[String]): Unit = {
    //获取spark的连接
    val conf: SparkConf = new SparkConf().setMaster("local[*]").setAppName("operator")
    val sc: SparkContext = new SparkContext(conf)
    //TODO groupBy 小功能：wordcount

    val rdd: RDD[String] = sc.textFile("datas/*.txt")

    val words: RDD[String] = rdd.flatMap(_.split(" "))

    val wordToOne: RDD[(String, Int)] = words.map((_, 1))

    val wordGroup: RDD[(String, Iterable[(String, Int)])] = wordToOne.groupBy(_._1)
    //val wordCount: RDD[(String, Int)] = wordGroup.map(kv => (kv._1, kv._2.size))
    //偏函数写法
    val wordCount: RDD[(String, Int)] = wordGroup.map {
      case (str, iter) => (str, iter.size)
    }

    wordCount.collect().foreach(println)
    sc.stop()
  }
}
